Multi-Omics Data Integration Analysis of an Immune-Related Gene Signature in LGG Patients With Epilepsy

• DOI: 10.3389/fcell.2021.686909
• Publication Date: 2021-07-16T11:40:12Z
• Authors: Quan Cheng; Weiwei Duan; Shiqing He; Chen Li; Hui Cao; Kun Liu; Weijie Ye; Bo Yuan; Zhiwei Xia
• Keywords: Nomogram

The tumor immune microenvironment significantly affects occurrence, progression, and prognosis, but its impact on the prognosis of low-grade glioma (LGG) patients with epilepsy has not been reported. Hence, purpose this study is to explore effect LGG epilepsy.The data derived from TCGA database. level cell infiltration proportion 22 cells were evaluated by ESTIMATE CIBERSORT algorithms, respectively. Cox LASSO regression analysis was adopted determine DEGs, further established clustering risk score models. association between genomic alterations investigated using CNV somatic mutation data. GSVA identify immunological pathways, inflammatory profiles related signature genes. Tumor Immune Dysfunction Exclusion (TIDE) algorithm GDSC database used predict patient's response immunotherapy chemotherapy, respectively.The associated score. Three prognostic DEGs (ABCC3, PDPN, INA) screened out. expression genes regulated DNA methylation. models could stratify into distinct groups. an independent predictor in a high risk-score indicating poor more malignant clinicopathological aberration features. nomogram had better predictive ability. Patients at higher macrophage increased activities T macrophages. While percentage NK CD56bright active activity B present low-risk patients. participated regulation immune-related such as IL6-JAK-STAT3 signaling, IFN-α response, IFN-γ TNFA-signaling-via-NFKB pathways. high-risk likely benefit anti-PD1 temozolomide (TMZ) treatment.An gene based ABCC3, INA, which can be status, chemotherapy epilepsy.